On the MUSIC-derived Approaches of Angle Estimation for Bistatic MIMO Radar

Abstract

We investigate the topic for the direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic multiple-input-multiple-output (MIMO) radar systems with the exploitation of array invariance. Several MUSICderived algorithms for angle estimation in MIMO radar have been presented and compared for their complexity costs against that of ESPRIT. The proposed scheme of multiinvariance multiple signal classification (MI-MUSIC) has the best performance and also can be considered as a generalization of MUSIC. Simulations verify the collaborative usefulness of our algorithm.

Covariance vector sparsity-aware DOA estimation for monostatic MIMO radar with unknown mutual coupling

“…In MIMO radar, the subspacebased methods, such as multiple signal classification (MUSIC) algorithm [8], estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm [9], have been proposed for angle estimation. In addition, by exploiting the special structure of the virtual array in monostatic MIMO radar with uniform linear array, the reduced dimensional ESPRIT (RD-ESPRIT) [10] and reduced dimensional Capon (RD-Capon) algorithm [11] are proposed to estimate DOA.…”

Coherent angle estimation in bistatic multi‐input multi‐output radar using parallel profile with linear dependencies decomposition

“…Utilising multiple antennas to propagate diverse waveforms and reflect parallel-processed signals, angles estimation in bistatic MIMO radar systems was firstly discussed in [3]. After that several algorithms for bistatic MIMO radar have been established for angle estimation [4][5][6][7][8][9][10][11]. Multiple signal classification (MUSIC) algorithm has been discussed in [4,5], which requires a spectral peak searching with a high computation cost, whereas estimation method of signal parameters via rotational invariance techniques (ESPRIT), which has exploited the invariance property for angle estimation in MIMO radar in [6][7][8], does not require the spectral peak searching.…”

“…Since multipath signals arise from the different propagation paths of the same target, their Doppler frequencies are identical and their radar cross-sections (RCS) are correlated random variables. Unfortunately, the algorithms' performances in [3][4][5][6][7][8][9][10][11] degrade with different levels in the presence of coherent sources. According to the coherent signal models, the coherency of sources will bring about rank loss in the covariance matrix of received data.…”

“…Obviously, the signal model established in(4) can be mapped to a PARALIND model[20,21]. Because both A r and A t are www.ietdl.org Vandermonde matrices, A r°At can be expressed as…”

Joint Estimation of Angle and Polarization for Bistatic MIMO Radar with Polarization Sensitive Array Using Dimension Reduction MUSIC

“…for direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in MIMO radar, which includes estimation of signal parameters via rotational invariance techniques (ESPRIT) [6][7][8], parallel factor algorithm [9], adaptive parallel factor algorithm [10], multiple signal classification (MUSIC) algorithm [11], Capon algorithm [12], and ESPRIT-MUSIC algorithm [13]. However, uniform arrays are required in the ESPRIT algorithm as well as eigenvalue decomposition.…”